A hybrid approach to enhance HbA1c prediction accuracy while minimizing the number of associated predictors: A case-control study in Saudi Arabia.
Type 2 diabetes (T2D) is considered a significant global health concern. Hemoglobin A1c level (HbA1c) is recognized as the most reliable indicator for its diagnosis. Genetic, family, environmental, and health behaviors are the factors associated with the disease. T2D is linked to substantial economi...
Saved in:
| Main Authors: | Faten Al-Hussein, Mali Abdollahian, Laleh Tafakori, Khalid Al-Shali |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0326315 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predicting Type 2 diabetes onset age using machine learning: A case study in KSA.
by: Faten Al-Hussein, et al.
Published: (2025-01-01) -
Impact of Virtual Clinics on Diabetes Distress and HbA1c Levels Among Patients with Diabetes Mellitus in Saudi Arabia
by: Mohammed A. Almarzooq, et al.
Published: (2025-01-01) -
Tooth Numbering System in Saudi Arabia: Survey
by: Sulieman S. Al-Johany
Published: (2016-10-01) -
Effects of thyroid status on HbA1c
by: Sivaranjani Ambalavanan, et al.
Published: (2024-11-01) -
Adherence to minimal retesting interval for HbA1c, vitamin D and thyrotropin in the University Hospital of Nepal
by: Saroj Thapa, et al.
Published: (2025-02-01)